Image Recognition and Augmented Reality in Cultural Heritage Using OpenCV

Cultural heritage often fails to represent a successful attraction because it is not able to capture the interest of tourists. Sometimes the presentation of an archaeological site cannot be improved because of legal or environmental constraints. Sometimes it is really difficult to recognize the relevant details or to understand its significance. A new way of exploiting archaeological sites in a more informative and intuitive way is needed. It is necessary to provide people with information and contents, for understanding the world around them, and with the possibility to interact with those places or objects in real time. Image recognition and analysis is a promising technology that can be applied in this field. In this paper we use in indoor, but also in outdoor scenarios, image recognition for the content discovery service. In particular search by sample facilities are speed-up and improved using a position based filtering. Moreover it is used to extract semantic from subjects in order to personalize the discovery and recommendation according to the user's profile.

[1]  Martin White,et al.  The EPOCH Multimodal Interface for Interacting with Digital Heritage Artefacts , 2006, VSMM.

[2]  Salvatore Venticinque,et al.  Distributed Agents Network for Ubiquitous Monitoring and Services Exploitation , 2009, 2009 International Conference on Computational Science and Engineering.

[3]  Salvatore Venticinque,et al.  Semantically Augmented Exploitation of Pervasive Environments by Intelligent Agents , 2012, 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications.

[4]  Salvatore Venticinque,et al.  Semantic Brokering of Multimedia Contents for Smart Delivery of Ubiquitous Services in Pervasive Environments , 2012, Int. J. Interact. Multim. Artif. Intell..

[5]  Didier Stricker,et al.  Archeoguide: first results of an augmented reality, mobile computing system in cultural heritage sites , 2001, VAST '01.

[6]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[7]  Salvatore Venticinque,et al.  Personalized Recommendation of Semantically Annotated Media Contents , 2013, IDC.

[8]  Salvatore Venticinque,et al.  BDI Intelligent Agents for Augmented Exploitation of Pervasive Environments , 2011, WOA.

[9]  Salvatore Venticinque,et al.  Mobile Devices for the Visit of "Anfiteatro Campano" in Santa Maria Capua Vetere , 2012, EuroMed.

[10]  Salvatore Venticinque,et al.  OVerFA: a collaborative framework for the semantic annotation of documents and websites , 2009, Int. J. Web Grid Serv..

[11]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[12]  Didier Stricker,et al.  Reality Filtering: A Visual Time Machine in Augmented Reality , 2008, VAST.